国际组织与成员国法律责任多重归属问题研究

国际组织和成员国的法律责任归属问题一直以来都是国际法争论的话题。政府间国际组织作为一类国际法主体,应独立承担法律责任。但在实践中,成员国在执行国际组织决议的过程中往往滥用国际组织法律人格,其行为不仅是国际组织法律人格的体现,还代表了自己的意志,造成法律责任归属不明。以此种争议情形为研究对象,结合1999年的使用武力合法性案,2007年欧洲人权法院的拜拉米案和萨拉马提(Behrami/Saramati)案、阿尔吉达(Al-Jedda)案以及2014年海牙法院关于斯雷布雷尼察(Srebrenica)诉荷兰案的相关判决,借鉴国外学者近几年的相关研究,认为应当坚持国际组织和成员国法律责任的多重归属。围绕责任多重归属原则的确立过程,通过对2011年《国际组织责任条款草案》相关条文的分析,明确了行为归属与责任归属的关系:只有确定行为归属之后,才能确定责任归属;为了最终确定责任的多重归属,提出以有效控制为标准认定行为归属,并明确这种有效控制是对具体行为的事实控制。     

Model Checks in Inverse Regression Models with Convolution‐Type Operators

Abstract. We consider the problem of testing parametric assumptions in an inverse regression model with a convolution‐type operator. An L ₂ ‐type goodness‐of‐fit test is proposed which compares the distance between a parametric and a non‐parametric estimate of the regression function. Asymptotic normality of the corresponding test statistic is shown under the null hypothesis and under a general non‐parametric alternative with different rates of convergence in both cases. The feasibility of the proposed test is demonstrated by means of a small simulation study. In particular, the power of the test against certain types of alternative is investigated. Finally, an empirical example is provided, in which the proposed methods are applied to the determination of the shape of the luminosity profile of the elliptical galaxy NGC 5017.     

论成品油定价机制中的有限规制：基于合谋的视角

利用单期静态博弈分析法、有限期动态博弈分析法和无限期动态博弈分析法对成品油定价机制中寡头厂商的合谋行为进行了分析。研究发现：两家寡头厂商在合谋条件下的收益均高于双方各自独立定产条件下的收益，因此，双方存在进行价格合谋的利益激励。基于此，我国成品油价格形成机制的改革可以考虑采用有限规制等手段。     

Comparing diagnostic tests: test of hypothesis for likelihood ratios

Likelihood ratios (LRs) are used to characterize the efficiency of diagnostic tests. In this paper, we use the classical weighted least squares (CWLS) test procedure, which was originally used for testing the homogeneity of relative risks, for comparing the LRs of two or more binary diagnostic tests. We compare the performance of this method with the relative diagnostic likelihood ratio (rDLR) method and the diagnostic likelihood ratio regression (DLRReg) approach in terms of size and power, and we observe that the performances of CWLS and rDLR are the same when used to compare two diagnostic tests, while DLRReg method has higher type I error rates and powers. We also examine the performances of the CWLS and DLRReg methods for comparing three diagnostic tests in various sample size and prevalence combinations. On the basis of Monte Carlo simulations, we conclude that all of the tests are generally conservative and have low power, especially in settings of small sample size and low prevalence.     

Monte Carlo comparison of five exponentiality tests using different entropy estimates

The paper studies five entropy tests of exponentiality using five statistics based on different entropy estimates. Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for each of the test statistics. By simulation, we compare the power of these five tests for various alternatives and sample sizes.     

An adaptive two-sample location-scale test of lepage type for symmetric distributions

For the two-sample location and scale problem we propose an adaptive test which is based on so called Lepage type tests. The well known test of Lepage (1971) is a combination of the Wilcoxon test for location alternatives and the Ansari-Bradley test for scale alternatives and it behaves well for symmetric and medium-tailed distributions. For the cae of short-, medium- and long-tailed distributions we replace the Wilcoxon test and the .Ansari-Bradley test by suitable other two-sample tests for location and scale, respectively, in oder to get higher power than the classical Lepage test for such distribotions. These tests here are called Lepage type tests. in practice, however, we generally have no clear idea about the distribution having generated our data. Thus, an adaptive test should be applied which takes the the given data set inio consideration. The proposed adaptive test is based on the concept of Hogg (1974), i.e., first, to classify the unknown symmetric distribution function with respect to a measure for tailweight and second, to apply an appropriate Lepage type test for this classified type of distribution. We compare the adaptive test with the three Lepage type tests in the adaptive scheme and with the classical Lepage test as well as with other parametric and nonparametric tests. The power comparison is carried out via Monte Carlo simulation. It is shown that the adaptive test is the best one for the broad class of distributions considered.     

Bayesian Network Structure Learning with Permutation Tests

In literature there are several studies on the performance of Bayesian network structure learning algorithms. The focus of these studies is almost always the heuristics the learning algorithms are based on, i.e., the maximization algorithms (in score-based algorithms) or the techniques for learning the dependencies of each variable (in constraint-based algorithms). In this article, we investigate how the use of permutation tests instead of parametric ones affects the performance of Bayesian network structure learning from discrete data. Shrinkage tests are also covered to provide a broad overview of the techniques developed in current literature.     

基于多维效应的能源效率评估理论——以非参数DEA方法为例

基于多维效应的能源效率评估使人们在达到经济增长目的的同时兼顾能源安全、竞争力、环境、社会和技术的可持续性。论述能源效率内涵演化发展的路径，在此基础上将能源效率的内涵扩展至多维效应。以非参数DEA（Data Envelopment Analysis）方法为例，研究基于多维效应的能源效率评估方法的演化与发展趋势。研究结果显示:采用DEA方法对基于多维效应的能源效率进行评估的发展趋势主要有以下3点:能源效率的内涵不断延伸；DEA模型向非导向非径向模型转变；能源效率评估的研究维度不断扩展。对多维效应的能源效率综合指标评价体系和评价方法还需做深入研究。     

Dependency and truncated forms of combinations in multivariate combination-based permutation tests and ordered categorical variables

ABSTRACT

Quite an important problem usually occurs in several multi-dimensional hypotheses testing problems when variables are correlated. In this framework the non-parametric combination (NPC) of a finite number of dependent permutation tests is suitable to cover almost all real situations of practical interest since the dependence relations among partial tests are implicitly captured by the combining procedure itself without the need to specify them [Pesarin F, Salmaso L. Permutation tests for complex data: theory, applications and software. Chichester: Wiley; 2010a]. An open problem related to NPC-based tests is the impact of the dependency structure on combined tests, especially in the presence of categorical variables. This paper’s goal is firstly to investigate the impact of the dependency structure on the possible significance of combined tests in cases of ordered categorical responses using Monte Carlo simulations, then to propose some specific procedures aimed at improving the power of multivariate combination-based permutation tests. The results show that an increasing level of correlation/association among responses negatively affects the power of combination-based multivariate permutation tests. The application of special forms of combination functions based on the truncated product method [Zaykin DV, Zhivotovsky LA, Westfall PH, Weir BS. Truncated product method for combining p-values. Genet Epidemiol. 2002;22:170–185; Dudbridge F, Koeleman BPC. Rank truncated product of p-values, with application to genomewide association scans. Genet Epidemiol. 2003;25:360–366] or on Liptak combination allowed us, using Monte Carlo simulations, to demonstrate the possibility of mitigating the negative effect on power of combination-based multivariate permutation tests produced by an increasing level of correlation/association among responses.